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Keyword: relationship, buffer effect, media choice, interpersonal closeness, communication goals
Abstract: The mediating nature of communication technologies (e.g., telephone, voice message, or chat) can buffer the experience of conversations by establishing a figurative shield between sender and receiver. From a psychological perspective, this buffer effect may affect senders’ communication channel choices depending on their respective communication goals. Building on the impression management model of strategic channel use (O’Sullivan, 2000), we examine how valence and locus of a message and the interlocutors’ relationship lead to differences in the buffer effect people establish through their channel choices. In two vignette-based, mixed-design studies, participants indicated which channel they would choose to communicate with a receiver in different situations, depending on the valence of the episode (positive vs. negative; Studies 1 and 2), who is at the center of the issue (self vs. other; Studies 1 and 2), and their interpersonal closeness (friend vs. acquaintance; Study 2). In Study 1, people chose channels with a higher buffer effect for negative (vs. positive) issues and episodes that focused on themselves (vs. the receiver). Study 2 supported a moderating effect of relationship. While people still chose channels with higher buffer effects for negative (vs. positive) issues in the acquaintance condition, the opposite was true when people were to communicate with friends. We attribute this to the higher salience of relational compared to self-presentational communication goals under increasing interpersonal closeness. The present studies expand the impression management model by focusing on the subjective buffer effect of communication channels and introducing the decisive role of relationship in its application. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
The text message – I understand it when a coach wants a different player (…) but there are ways of going about it. You don’t do it by text message. You should be honest and direct to someone’s face. (…) I was showing it to my team-mates and they could not believe how he had done it.(Crafton, 2017, para. 36-38)This quote from an interview with professional footballer Diego Costa captures the soccer player’s disappointment with his dismissal. Regardless of whether he expected to be released or not, Costa, as well as his teammates, felt that a text message was an inappropriate way of releasing someone. After all, face-to-face communication is widely considered the ideal way to end relationships: it allows for a conversational back-and-forth, the transmission of nonverbal cues, and extensive explanations (Gershon, 2008).
But on the other hand, Antonio Conte, his coach at that time, found himself in a difficult situation. Conveying negative messages is never easy and comes with a certain distress. People tend to anticipate receivers’ reactions and therefore hesitate to share such messages – also known as the MUM effect (keeping mum about undesirable messages; Rosen & Tesser, 1970; Tesser & Rosen, 1975). Releasing Costa via text message instead of talking to him might have buffered Conte’s distress, since mediated communication channels offer a less threatening environment to deliver negative content (Derks & Bakker, 2010; Kafetsios et al., 2017; Watts, 2007).
Such discrepancies between receivers’ expectations and senders’ channel choices yield the question of how people decide between available channels in the face of challenging interpersonal communication – if senders’ choices actually do reflect an intention to buffer the communication experience and whether this varies depending on people’s relationships.
In the present work, we build on the impression management model of strategic channel use (O’Sullivan, 2000). But instead of “lumping all forms of computer-mediated communication (CMC) together or considering diverse channels in a monolithic fashion” (Fox & McEwan, 2017, p. 1), which Fox and McEwan criticized previous research of doing, we focus on how people experience a certain characteristic of different communication channels, namely, their subjective buffer effect. Although approaches such as media richness or social presence theory also highlight specific characteristics and affordances of different communication channels, they are seldom appropriately operationalized in study design (Fox & McEwan, 2017). It is rarely tested if, and when, people’s individual perception and theoretically assumed experiences are actually reflected in choices of communication channels.
In the first study of the present research, we adapt the work of O’Sullivan (2000) but account for some shortcomings of the original design and integrate the notion of a subjective buffer effect of communication channels. In the second study, we introduce a crucial variable, not explicitly considered in the former model, by exploring the influence of interpersonal closeness. Based on our observations, we theorize about an underlying shift from self-presentational to relational communication goals. But first, we present a concise summary of the impression management model, interactional control through channel choice, and the potential role of interpersonal closeness.
The Impression Management Model
We predicate our work upon a theoretical framework that applies to the strategic choice of communication channels: O’Sullivan’s (2000) impression management model (IMM). It builds on the premise that impression management, that is, the attempt of individuals to influence what others think about them, is a key component of interpersonal interactions (Goffman, 1959; Schlenker, 2013) and that the choice of communication channel is one interactional strategy to achieve this. Briefly, the IMM proposes that people’s preference for mediated channels increases as soon as a communication episode threatens one’s self-presentation, since those channels provide more control over the exchange of information (Ledbetter & Herbert, 2020).
Specifically, the model focuses on all instances where one’s own or a relational partner’s self-concept is potentially threatened or supported, labeled “self-presentationally relevant episodes.” Such an episode is characterized by its valence and locus, that is, whether the episode is perceived as positive or negative (i.e., valence) and whether the issue impacts the presentation of oneself or the other (i.e., locus). Based on these factors, a communication goal is formulated under the premise of maximizing rewards and minimizing costs. To pursue this goal, the model proposes that the sender adapts the message’s content accordingly and chooses the communication channel on the basis of its symbolic meaning (e.g., email as a formal and text messaging as an informal medium), one’s own social skills (i.e., the general ability to handle interactions over a specific channel) and the interactional control a channel provides (e.g., the capacity to control the duration and nature of exchanged information). Following the communicative act, the episode is evaluated by those involved and, in turn, evaluations of their relationship and respective self-concepts are shaped. In support of the model, an initial investigation (O’Sullivan, 2000) showed people’s preferences for CMC over face-to-face conversation when they imagined an episode that could threaten a positive impression (i.e., negative valence) and when the issue was of concern to their own rather than the partner’s image (i.e., self-locus).
Feaster (2010) later advanced this model by focusing not on channel features themselves but on each individual’s ability to exercise information control via the channel in order to maintain face, that is, their desired personal image (Goffman, 1959). Every interpersonal interaction can potentially affect an involved person’s face (Brown & Levinson, 1987) but people differ in their individual competence to exert expressive control (i.e., ability to control the flow of revealed information) and privacy control (i.e., ability to withhold information) over a certain channel in face-threatening acts (Feaster, 2010).
Interactional Control and Communication Goals
Channel choice as a means to strategically control interaction has been the focus of several works in the past (Bülow et al., 2019; Kayany et al., 1996; Tretter & Diefenbach, 2020). However, while O’Sullivan (2000) and Feaster in particular (2010) emphasized the value of channels for active self-presentation, there is also a receiving role in communication. For example, sending negative content via email offers the opportunity to deliberately craft responses (due to its asynchronous nature) but it may also attenuate the experience of receiving distressing responses (due to the lack of nonverbal cues).
Accordingly, communication channels may also vary in their ability to shield oneself from the other and avoid direct exposure (Riordan & Kreuz, 2010). O’Sullivan (2000) mentioned this shielding capacity that “would help insulate the interaction initiator from the distressing reactions” (p. 414), labeling it a “buffer” effect (Derks & Bakker, 2010; Sussman & Sproull, 1999; Watts, 2007; Wotipka, 2016). We aim to add to work on the IMM by applying a subjective buffer effect measure that also accounts for this channel capacity while considering that not all channels are equally able to avoid exposure (e.g., video chat might even be perceived as more exposing than real-life conversations).
To this end – and in line with the rationale that people perceive channels differently and vary in their ability to utilize them for communication purposes (J. R. Carlson & George, 2004; Feaster, 2010; Markus, 1994) – we will not compare people’s channel choices per se but the buffer effect each individual attributes to the chosen channel. Basically, we presume that this subjective buffer effect is determined by an individual’s general perception of a communication channel. Contextual factors, however, contribute to whether a channel with a relatively high or low subjective buffer effect is chosen.
According to the IMM, people choose channels strategically when an episode potentially affects their own or the partner’s self-presentation. However, besides self-presentational goals, relational goals (e.g., to maintain or escalate a relationship) are a key aspect of interpersonal communication as well (Canary et al., 2008). Moreover, mutual concern for both partners and the constructed image of the relationship is inadequately represented within the model, given the association of mutual concerns with the likelihood of using a certain channel in interpersonal conflicts (Ledbetter & Herbert, 2020). Accordingly, we intend to account for such relational communication goals by considering interlocuters’ interpersonal closeness in our approach.
Research Approach and Propositions
Our research examines interpersonal communication situations that hold the potential to elicit self-presentational as well as relational communication goals. To provide a better understanding of people’s channel choices in those situations, we focus on the subjective buffer effect of communication channels instead of their allegedly objective characteristics. To this end, we build on the IMM (O’Sullivan, 2000) but extend the original study by investigating whether people’s channel choices actually reflect differences in buffer effects (Study 1) and by examining variation depending on the relationship between the persons involved (Study 2). While O’Sullivan lumped preferences for all CMC channels together, we follow a characteristic rather than holistic approach (Fox & McEwan, 2017; Westerman et al., 2019; Westerman & Westerman, 2013), which also accounts for changes in channel perceptions over the last two decades. Conceptually, we apply the IMM classification of episodes along the general dimensions of valence (i.e., positive or negative) and locus (i.e., affecting one’s own or the other’s self-presentation). Their combination leads to four possible situations labeled “confess,” “boost,” “accuse,” or “praise” (see Table 1).
Image transcription text
Locus Self Other Valence Positive Boost Praise Negative Confess
Accuse Note. Adapted from O’Sullivan (2000). Classification of
situations by valence and locus
Our research is predicated on two central propositions stemming from the literature outlined earlier. First, people attribute different buffer effects to the same channels. Therefore, we compare channel choices based on their individually assigned buffer effect instead of channel choices themselves. Second, depending on the message (i.e., valence and locus) and the relationship with the receiver (i.e., interpersonal closeness), people pursue different communication goals (e.g., self-presentational, relational), for which a buffer effect is advantageous or detrimental. Thus, differences in situational characteristics (and underlying communication goals) should be represented in the subjective buffer effect of the channel an individual chooses, as further explicated in the next section.
Valence of the Episode
Research on the MUM effect is pertinent to propositions about the effect of positive and negative messages on channel choice. It proposes essentially two main explanations for people’s unwillingness to transmit bad news: public presentation or private discomfort (Bond & Anderson, 1987; Dibble, 2018). On the one hand, people might be reluctant to share bad news due to their fear of being evaluated negatively by the recipient (i.e., public explanation), while, on the other hand, they might hesitate since they feel bad about eliciting negative affect in the receiver (i.e., private explanation). Although there is also research indicating private discomfort and a concern for the other, a majority of studies support the former (Dibble, 2018). More importantly, the delivery of bad news can pose a threat to the face of the sender as well as the receiver (Dibble et al., 2015). Mediated channels might buffer such inherent face-threats, as people were shown to communicate more accurately and honestly over computer-mediated channels than face-to-face situations (Sussman & Sproull, 1999). On the other hand, in the case of positive news, the communication channel may be moot (Dibble, 2018; Sussman & Sproull, 1999), people might even seek a more immediate experience (Tretter & Diefenbach, 2020). We expect this to be represented in the choice of channels with a higher buffer effect in negative episodes.
Hypothesis 1 (H1): Senders choose communication channels with a higher subjective buffer effect in negative (vs. positive) interpersonal communication situations.
Locus of the Issue
Assumptions about the role of the buffer effect in episodes of different locus are somewhat less obvious, since face-relevant situations might always affect both parties’ self-presentation. However, in negative situations, we assume that people choose channels with a higher buffer effect for self-locus than other-locus situations for two reasons: first, the negatively valenced episodes of our paradigm, “confess” and “accuse,” represent two instances that Brown and Levinson (1987) characterize as primarily threatening the speaker’s or the hearer’s face, respectively (Wilson et al., 1998). Second, people reportedly feel more reluctant when they are themselves the locus of the situation (Dibble & Sharkey, 2017). Regarding positive situations, we expect a similar effect of locus for another two reasons: First, Brown and Levinson (1987) compared the face threat of bringing good news about oneself (because it also indicates little care for the other) with the delivery of bad news about the recipient, an act which reportedly elicits reluctance. Second, although compliments (or “praises”) are face-enhancing for the receiver, self-praise (or “boost”) poses a threat to the sender’s face by appearing egocentric (Matley, 2018). Channels with higher buffer effects are supposed to mitigate the outlined face-threats predominating in self-locus episodes.
Hypothesis 2 (H2): Senders choose communication channels with a higher subjective buffer effect in interpersonal communication situations that focus on themselves (vs. the receiver).
Relationship of the Interlocuters
Considering the impact of closeness on the choice of channels, we expect analogous valence and locus effects in distant relationships, since the basic tendencies outlined earlier presumably remain unaltered by a decline in closeness. In close relationships, however, the concern for self-presentation decreases (Brown & Levinson, 1987), self-oriented motives fade (Dubois et al., 2016), and the transmission of bad news is more likely (Weenig et al., 2001). Moreover, a concern for the relationship itself, instead of self or other, might be decisive in close relationships (Ledbetter & Herbert, 2020), leading to the avoidance of buffering media out of considered appropriateness (Westerman & Westerman, 2010; Westerman & Westerman, 2013), moral responsibility (Weenig et al., 2014), or as a means to signal the strength of the relationship (Dibble & Sharkey, 2017). Thus, although reluctance in the delivery of bad news has also been reported equally for friends and strangers (Dibble & Levine, 2013) and different channels (Dibble, 2018), we do not expect this reluctance to be represented in the actual choice of channels. On the contrary, we even assume channel choices with a lower buffer effect for negative (vs. positive) messages in close relationships. More specifically, we suppose that people do not primarily focus on short-term benefits (e.g., buffering negative conversations) but on what seems adequate to preserve the close relationship in the long run (e.g., upright conflict resolution). Therefore, in close relationships, a subjectively less-buffered communication process might seem even more desirable for negative than for positive messages.
Hypothesis (H3): There is an interaction effect between the valence of the episode and interpersonal closeness on channel choice.
Hypothesis 3a (H3a): In distant relationships, senders choose communication channels with a higher subjective buffer effect in negative (vs. positive) interpersonal communication situations.
Hypothesis 3b (H3b): In close relationships, senders choose communication channels with a lower subjective buffer effect in negative (vs. positive) interpersonal communication situations. Assumptions on the potential interplay between closeness and locus are considerably more tentative due to the lack of empirical studies considering both. However, as the locus hypotheses mainly build on the protection of self-face and since face concerns are less salient in closer relationships (Brown & Levinson, 1987), we expect these particular locus effects only to appear in distant relationships. In closer relationships, however, where the self-other distinction fades (Aron et al., 1992), we expect an increasing focus on the mutually held image of the relationship (Ledbetter & Herbert, 2020) and less use of the self-presentational advantages of channels (Ruppel, 2015). Therefore, we propose a shift toward choices with a lower buffer effect for self-locus episodes, as this symbolically conveys the importance of the relationship (Dibble & Sharkey, 2017; Ledbetter & Herbert, 2020), all the more so in cases of confessions. We assume a similar shift in positive episodes with friends, since face concerns (e.g., the fear of appearing egocentric) drop and one might be more inclined to reduce buffering when receiving praise than when praising others.
Hypothesis 4 (H4): There is an interaction effect between the locus of the issue and interpersonal closeness on channel choice.
Hypothesis 4a (H4a): In distant relationships, senders choose communication channels with a higher subjective buffer effect in interpersonal communication situations that focus on themselves (vs. the receiver).
Hypothesis 4b (H4b): In close relationships, senders choose communication channels with a lower subjective buffer effect in interpersonal communication situations that focus on themselves (vs. the receiver). Study 1 closely follows the design of the study by O’Sullivan (2000; i.e., varying valence and locus) to test how the initial study transfers to today’s conditions and whether people’s channel choices generally reflect differences in buffer effects (Hypotheses 1 and 2), before a relationship variation is added in Study 2 to examine Hypotheses 3 and 4 regarding interpersonal closeness.
Study 1
Method
Experimental Design
Study 1 applied a 2 (valence: positive vs. negative) × 2 (locus: self vs. other) within-subjects design and was conducted online. The four vignettes used by O’Sullivan (2000) were translated to German and slightly adapted to describe episodes of communication with a friend. For example, the vignette in the “confess” condition read the following: “Think for a minute about a topic, issue, or incident that would undermine how a friend thinks about you. For example, it could be a discussion about you failing to meet his or her expectations, you doing something morally distasteful, you holding an opinion you know your friend would find repugnant, you being disloyal toward your friend, etc.”
Participants
Participants were recruited via institutional mailing lists including students and working people. A total of 122 participants (31% male, 69% female), aged between 17 and 63 years (M = 26.87; SD = 10.13; Mdn = 24), completed the online survey. Students received course credit for their participation, while other participants could take part in a lottery for five 10 Amazon vouchers.
Procedure
After confirming an initial consent agreement, participants were introduced to the upcoming procedure. They were presented with each of the four vignettes in a randomized order. For each vignette, they subsequently indicated which communication channel they would choose and provided an affect rating of the previously encountered situation. After all four vignettes were completed, participants rated each of the available communication channels according to their subjective buffer effect. Since we presume that individual perception of a channel’s buffer effect does not substantially vary across contexts, this assessment was conducted independently of the actual decision situations (Feaster, 2013). Finally, participants reported basic demographic data (age, gender).
Measures
Channel Choice
Participants were given seven different communication channels to choose between: email, text message, instant messaging/chat (e.g., WhatsApp, Threema, Facebook Messenger), voice message/voice mail (e.g., voice messaging services, mobile phone mailbox, answering machine), telephone, video chat (e.g., Skype, Facetime), or face-to-face conversation. The rationale behind this selection was to provide participants with the most common ways of communication while covering a broad spectrum of potentially varying buffer effects.
Subjective Buffer Effect
Six items (see Appendix) were used to assess the buffer effect participants attribute to the available communication channels on a scale from 1 (= not at all) to 5 (= very much; Wotipka, 2016). Reliability analyses yielded acceptable to mainly good internal consistencies for overall buffer scores of each available channel (see Table 2).
Image transcription text
Channel n M SD Cronbach’s a Email 122 3.14 0.83 788 Text
message 122 2.57 0.85 .852 Instant messaging/chat 121 2.58
0.80 .835 Voice message/voice mail 122 2.09 0.82 .87…
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Affect
To obtain insights into the affective reaction that we expected the vignettes to induce, a nine-point scale version of the self-assessment manikin scale (SAM) was applied (Bradley & Lang, 1994). This well-established measure comprises three facets of affective experience (pleasure, arousal, dominance). Instead of using verbal anchors, affect is assessed by allocating each point of the scale to an abstract pictorial representation of intensity. For example, the pleasure scale starts with a picture of a frowning face and ends with a happily smiling figure, while the middle of the scale indicates a neutral state. Depending on the valence of the episode, participants should report different degrees of pleasure, that is, higher pleasure for positive (boost, praise) compared to negative episodes (confess, accuse). Depending on the locus of the message, participants should report different degrees of arousal, that is, higher arousal for self-related (boost, confess) compared to other-related messages (praise, accuse). Therefore, the SAM was used to assess the validity of the applied vignettes by assessing affective states (e.g., unpleasant arousal in negative, self-related situations) that we assume might underlie people’s consideration of subjective buffer effects.
Results
Initially, the self-assessment manikin scales were consulted to examine whether affective reactions varied across vignettes as expected. The mean pleasure values for the confess (M = 2.66, SD = 1.48) and accuse conditions (M = 3.29, SD = 1.53) were significantly lower than for the boost (M = 7.53, SD = 1.75) and praise conditions (M = 7.64, SD = 1.57), F(1, 120) = 568.07, p < .001, ?p2 = 0.83. Furthermore, participants were more aroused when the issue focused on themselves (confess: M = 6.46, SD = 1.97; boost: M = 4.45, SD = 2.28) than when it focused on the other (accuse: M = 6.06, SD = 1.88; praise: M = 3.85, SD = 1.91), F(1, 119) = 15.62, p < .001, ?p2 = 0.12. Taking together these patterns of reported pleasantness and arousal, the manipulation led to the expected effects on participants' affective states. Table 3 shows the frequencies of choices and descriptive statistics of subjective buffer scores for each communication channel within the four experimental conditions. An initial visual inspection already indicates that the tendencies suggested by the IMM (e.g., more CMC for negative vs. positive messages) are not necessarily reflected in the mere channel choice frequencies, but in the affordances these channels provide, that is, their subjective buffer effects. For example, the mean buffer scores across chosen channels are mostly higher in the negative than positive valence conditions, indicating a tendency toward choices that come with a higher subjective buffer effect. Image transcription text Condition Confess Boost Accuse Praise Channel F M (SD) F M (SD) F M (SD) M (SD) Email 9 3.48 (0.99) 6 3.06 (1.14) 6 3.25 (1.14) 4 2.04 (1.29) Text message 2 3.17 (0.24) 4 3.17 (0.69) 3... Show more Furthermore, since an individual's choice of the same channel in several situations would always come with the same buffer, differences between situations allow for interesting comparisons between groups. For example, those participants who chose email in negative situations (i.e., confess, accuse) might also generally associate a higher buffer effect with it than people who chose the same channel in positive valence situations (i.e., boost, praise). Taken together, this indicates that people may differ in their individual perception of the same channel, but congruently choose a channel that - for them - comes with a higher buffer effect in negative situations. Accordingly, the buffer effect could be more informative than the channel itself to explain choices in interpersonal communication situations. The following statistical analysis explored this psychological pattern on a more general level. To this end, we conducted a two-way repeated-measures ANOVA that considers the buffer effect people associate with their choices rather than simply comparing choices themselves. In line with H1, there was a statistically significant main effect of valence, F(1, 121) = 9.42, p = .003, ?p2 = 0.07, indicating that people chose a communication channel with a higher buffer effect when communicating negative messages (M = 2.45, SE = 0.07) versus positive messages (M = 2.25, SE = 0.07). Furthermore, in line with H2, a significant main effect of locus emerged, F(1, 121) = 4.28, p = .041, ?p2 = 0.03, implying that people chose channels with a higher buffer effect for communication focusing on themselves (M = 2.41, SE = 0.07) rather than on the receiver (M = 2.29, SE = 0.07). There was no significant interaction effect between valence and locus of the message, F(1, 121) = 0.06, p = .813, ?p2 < 0.01. Discussion While former research on the buffer effect typically considered CMC as a single category in contrast to face-to-face conversations, our study applied a new and more differential approach. We treated communication channels separately according to the buffer effect each individual associates with them. In line with our hypotheses, participants tended toward communication channels with a higher buffer effect when they were to communicate negative messages (valence effect) and when the issue involved themselves (locus effect). We argue that this is due to the potential of the buffer effect to avoid unpleasant experiences and achieve beneficial self-presentation. However, since communication inherently involves others, the interpersonal closeness between sender and receiver and activated relational goals might also play a role in senders' channel choices. Therefore, in a second step, we extended the research design and considered interpersonal closeness by including different kinds of relationships. Study 2 Method Experimental Design We conducted an online experiment similar to Study 1 but added the relationship between sender and receiver as an additional factor. This led to a 2 × 2 × 2 mixed design with valence (positive vs. negative) and locus (self vs. other) as within-subject factors and interpersonal closeness (friend vs. acquaintance) as the between-subjects factor. Two separate sets of the four vignettes adapted from the work of O'Sullivan (2000) were applied, one set asking the participants to imagine communication with a close friend and the other set communication with an acquaintance. Furthermore, participants only rated the buffer effects of those channels they had previously chosen in at least one of the described situations. Participants Participants were recruited via institutional mailing lists including students as well as working people and through Clickworker, a German-based crowd-working platform similar to Amazon Mechanical Turk. Since there was no effect of data source on the key variables, the two samples were collapsed. The in
